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A cloud native embedded storage engine built on object storage.

Project description

SlateDB

PyPI ReadTheDocs Python Versions GitHub License slatedb.io Discord

Introduction

SlateDB is an embedded storage engine built as a log-structured merge-tree. Unlike traditional LSM-tree storage engines, SlateDB writes data to object storage (S3, GCS, ABS, MinIO, Tigris, and so on). Leveraging object storage allows SlateDB to provide bottomless storage capacity, high durability, and easy replication. The trade-off is that object storage has a higher latency and higher API cost than local disk.

To mitigate high write API costs (PUTs), SlateDB batches writes. Rather than writing every put() call to object storage, MemTables are flushed periodically to object storage as a string-sorted table (SST). The flush interval is configurable.

put() returns a Future that resolves when the data is durably persisted. Clients that prefer lower latency at the cost of durability can instead use put_with_options with await_durable set to false.

To mitigate read latency and read API costs (GETs), SlateDB will use standard LSM-tree caching techniques: in-memory block caches, compression, bloom filters, and local SST disk caches.

Checkout slatedb.io to learn more.

Installation

pip install slatedb

Requirements

  • Python 3.10 or higher

Features

  • Support for in-memory object store and object stores (S3, GCS, ABS, MinIO, memory)
  • Sync and async APIs
  • Range scans with iteration and seek
  • Snapshots for consistent, read-only views
  • Transactions with snapshot isolation (SI) and serializable snapshot isolation (SSI)
  • Atomic batched writes
  • Merge operator (user-defined Python callable)
  • Per-operation time-to-live (TTL)
  • Reader for read-only access with optional checkpoint pinning
  • Admin APIs for manifests, checkpoints, clones, garbage collection, and sequence↔timestamp mapping

Usage

The example below demonstrates common features in a single script.

from __future__ import annotations

from slatedb import (
    SlateDB,
    SlateDBReader,
    SlateDBAdmin,
    WriteBatch,
)


# Optional: define a merge operator. This example concatenates values.
def concat(key: bytes, existing: bytes | None, value: bytes) -> bytes:
    return (existing or b"") + value

# Open a database using the in-memory object store
db = SlateDB("/tmp/slatedb-demo", url="memory:///", merge_operator=concat)

# Basic CRUD
db.put(b"user:1", b"Alice")
assert db.get(b"user:1") == b"Alice"

# Per-op TTL and durability control
db.put_with_options(b"temp", b"ok", ttl=5_000, await_durable=False)

# Batched writes
wb = WriteBatch()
wb.put(b"batch:1", b"one")
wb.delete(b"temp")
db.write(wb)

# Transactions (SSI or SI). Operations buffer until commit.
txn = db.begin("ssi")
txn.put(b"user:2", b"Bob")
txn.merge(b"counter:visits", b"1")  # uses the configured merge operator
txn.commit()

# Snapshots provide consistent, read-only views
snap = db.snapshot()
assert snap.get(b"user:2") == b"Bob"

# Range scans (prefix scan when end omitted). Iterator supports seek.
it = db.scan(b"user:")
first = next(it)
it.seek(b"user:2")
rest = list(it)

# Advanced scan options (read-ahead, caching, durability filter)
_ = list(db.scan_with_options(b"user:", cache_blocks=True, read_ahead_bytes=1 << 20))

# Flush
db.flush_with_options("wal")

# Get metrics
metrics = db.metrics()

# Create a durable checkpoint and read it with a read-only reader
ckpt = db.create_checkpoint(scope="durable")
reader = SlateDBReader("/tmp/slatedb-demo", url="memory:///", checkpoint_id=ckpt["id"])
_ = list(reader.scan(b"user:"))
reader.close()

# Admin: list checkpoints, read manifests, GC, and sequence/timestamp mapping
admin = SlateDBAdmin("/tmp/slatedb-demo", url="memory///")
_ = admin.list_checkpoints()
_ = admin.read_manifest()
admin.run_gc_once(manifest_min_age=0, wal_min_age=0, compacted_min_age=0)

db.close()

Contributing

SlateDB's Python bindings use uv to manage the development environment. You can install uv following the steps on its website. Once you've installed uv, run uv venv to create a virtual environment.

Installing dependencies

Run uv pip install to install all dependencies. If you only want test dependencies, you can run uv pip install -e .[test].

Running tests

Run uv run pytest to run all tests.

Building the project

SlateDB's Python bindings use Maturin to link the Rust codebase with the Python codebase.

  1. Install Maturin by running uv tool install maturin.
  2. Build the project with Maturin by running uv run maturin develop.

License

SlateDB is licensed under the Apache License, Version 2.0.

Foundation

SlateDB is a member of the Commonhaus Foundation.

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SHA256 9acea98fcdd95fb9a360cc43ff0ced508d960b4c88a5436710ccd8d2d66b83d2
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SHA256 0d18366f2a43c073dc302881b5eeadcc6ba6de9fc459d46e70abdc1121b521de
MD5 c1a9d5d3b8acdc48e2df7205945f4964
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SHA256 202303013ccaf94f004df2d5542676631f39d1a587bd2153309542e5dc7ae00e
MD5 499337010e7b518eb6446b3a3cbc2b2e
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SHA256 60ed30cba94f1c4854fb0017caed4e22d79cae37ba9b6cbf1a249c5e81e484a7
MD5 dbfb8115348ddf24a06a0be1470c5966
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MD5 37dde7de59c244f57d4017fd08414371
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MD5 e69e9af5bdd04a3f806fbb6564ada51f
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MD5 ec45136e7d4f088661aafbe01745fb8c
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SHA256 ef267446afab1ddc59af475a34cf3770172a1e57064b34c09c68f76c4e87fdca
MD5 6c50e5c722fe131c591fe6a3d0243363
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MD5 89f0bebb68e3b9456eb55c8b89d156f8
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SHA256 cdbd780ba71006305677e5f6255ff37b8b7ecb9ebc15c4039b1e8c6baf83226b
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SHA256 4024a98852b6af42cc273de29ec0f82d1290552b10f287cf2e5815c6531aeaad
MD5 0392f56b78d69d29920dff9eec15dfb0
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